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Decentralised distributed multiple objective particle swarm optimisation using peer to peer networks

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4 Author(s)
Scriven, I. ; Sch. of Eng., Griffith Univ., Brisbane, QLD ; Lewis, A. ; Ireland, D. ; Junwei Lu

This paper describes a distributed particle swarm optimisation algorithm (PSO) based on peer-to-peer computer networks. A number of modifications are made to the more traditional synchronous PSO algorithm to allow for fully decentralised, scalable and fault-tolerent operation. The modified algorithm uses staggered propagation of objective-space knowledge between sub-swarms to eliminate the need for a centralised data store. Analytical test functions are used to examine the performance of the proposed algorithm and its variations in comparison with a basic synchronous PSO implementation. The results clearly show the feasibility of decentralised particle swarm optimisation.

Published in:

Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on

Date of Conference:

1-6 June 2008